Anxiety Sensitivity Mediates Relations Between Attachment and Aggression Differently by Gender
Bibliographic record
Abstract
The present study examined relations among attachment, aggression, and anxiety sensitivity (AS) in a sample of male and female undergraduates. Given that some individuals may use aggression to modulate negative emotional states, it was predicted that AS dimensions would mediate relations between attachment anxiety (vs. attachment avoidance) and certain forms of aggression, particularly impulsive aggression. Moreover, it was hypothesized that the relations among attachment, aggression, and AS would be moderated by gender. Participants ( N = 1,042) completed measures of attachment (Experiences in Close Relationships–Revised [ECR-R]), aggression (Aggression Questionnaire [AQ]; Impulsive/Premeditated Aggression Scales [IPAS]), and AS (AS Index–3 [ASI-3]). Results indicated that AS mediated relations between attachment dimensions (both anxiety and avoidance) and most forms of aggression, with each of the AS dimensions playing a unique role differentially by gender. Cognitive concerns emerged as a significant mediator, particularly for men; physical and social concerns played more of a mediating role for women. Interestingly, none of the AS dimensions played a significant mediating role between attachment (either anxiety or avoidance) and physical aggression for men. Results are discussed in terms of their clinical implications and directions for future research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".